Stochastic Description of Dynamical Traps in Human Control

Abstract

A novel model for dynamical traps in intermittent human control is proposed. It describes probabilistic, step-wise transitions between two modes of a subject's behavior - active and passive phases in controlling an object's dynamics - using an original stochastic differential equation. This equation governs time variations of a special variable, denoted as $\zeta$, between two limit values, $\zeta=0$ and $\zeta=1$. The introduced trap function, $\Omega(\Delta)$, quantifies the subject's perception of the object's deviation from a desired state, thereby determining the relative priority of the two action modes. Notably, these transitions - referred to as the subject's action points - occur before the trap function reaches its limit values, $\Omega(\Delta)=0$ or $\Omega(\Delta)=1$. This characteristic enables the application of the proposed model to describe intermittent human control over real objects.